Source code for liif_test_config

# Copyright (c) OpenMMLab. All rights reserved.
from mmengine.dataset import DefaultSampler

from mmagic.datasets import BasicImageDataset
from mmagic.datasets.transforms import (GenerateCoordinateAndCell,
                                        LoadImageFromFile, PackInputs,
                                        RandomDownSampling)
from mmagic.engine.runner import MultiTestLoop
from mmagic.evaluation import PSNR, SSIM

[docs]scale_test_list = [2, 3, 4, 6, 18, 30]

[docs]test_pipelines = [[
    dict(
        type=LoadImageFromFile,
        key='gt',
        color_type='color',
        channel_order='rgb',
        imdecode_backend='cv2'),
    dict(type=RandomDownSampling, scale_min=scale_test, scale_max=scale_test),
    dict(type=GenerateCoordinateAndCell, scale=scale_test, reshape_gt=False),
    dict(type=PackInputs)
] for scale_test in scale_test_list]

# test config for Set5
[docs]set5_dataloaders = [
    dict(
        num_workers=4,
        persistent_workers=False,
        drop_last=False,
        sampler=dict(type=DefaultSampler, shuffle=False),
        dataset=dict(
            type=BasicImageDataset,
            metainfo=dict(dataset_type='set5', task_name='sisr'),
            data_root='data/Set5',
            data_prefix=dict(img='LRbicx4', gt='GTmod12'),
            pipeline=test_pipeline)) for test_pipeline in test_pipelines
]
[docs]set5_evaluators = [[
    dict(type=PSNR, crop_border=scale, prefix=f'Set5x{scale}'),
    dict(type=SSIM, crop_border=scale, prefix=f'Set5x{scale}'),
] for scale in scale_test_list]

# test config for Set14
[docs]set14_dataloaders = [
    dict(
        num_workers=4,
        persistent_workers=False,
        drop_last=False,
        sampler=dict(type=DefaultSampler, shuffle=False),
        dataset=dict(
            type=BasicImageDataset,
            metainfo=dict(dataset_type='set14', task_name='sisr'),
            data_root='data/Set14',
            data_prefix=dict(img='LRbicx4', gt='GTmod12'),
            pipeline=test_pipeline)) for test_pipeline in test_pipelines
]
[docs]set14_evaluators = [[
    dict(type=PSNR, crop_border=scale, prefix=f'Set14x{scale}'),
    dict(type=SSIM, crop_border=scale, prefix=f'Set14x{scale}'),
] for scale in scale_test_list]

# test config for DIV2K
[docs]div2k_dataloaders = [
    dict(
        num_workers=4,
        persistent_workers=False,
        drop_last=False,
        sampler=dict(type=DefaultSampler, shuffle=False),
        dataset=dict(
            type=BasicImageDataset,
            ann_file='meta_info_DIV2K100sub_GT.txt',
            metainfo=dict(dataset_type='div2k', task_name='sisr'),
            data_root='data/DIV2K',
            data_prefix=dict(
                img='DIV2K_train_LR_bicubic/X4_sub', gt='DIV2K_train_HR_sub'),
            pipeline=test_pipeline)) for test_pipeline in test_pipelines
]
[docs]div2k_evaluators = [[
    dict(type=PSNR, crop_border=scale, prefix=f'DIV2Kx{scale}'),
    dict(type=SSIM, crop_border=scale, prefix=f'DIV2Kx{scale}'),
] for scale in scale_test_list]

# test config
[docs]test_cfg = dict(type=MultiTestLoop)
[docs]test_dataloader = [
    *set5_dataloaders,
    *set14_dataloaders,
    *div2k_dataloaders,
]
[docs]test_evaluator = [
    *set5_evaluators,
    *set14_evaluators,
    *div2k_evaluators,
]